Many communications devices are becoming equipped with low-cost image acquisition capability. For instance, many cell phones now incorporate digital cameras, and many pocket personal computers (PPCs), and personal digital assistants (PDAs) have image acquisition and communications options. As such devices proliferate, a number of applications become possible in which such devices are networked to provide a distributed imaging capability.
For instance, a group of cameras equipped with wireless communications capability can be placed on the walls in and around a building, then networked together to form a surveillance system covering the exterior and interior of the building. Such a rapidly deployable surveillance system may be used, for instance, by military personnel securing a target, or by an emergency response team responding to an incident such as a fire or an accident.
In another application, a network of communications-enabled cameras distributed around a sporting event may provide an imaging network capable of capturing the motion and positions of players in three dimensions. This information may be useful for transmission of the game over the internet or for post-game analysis of player performance.
Such a network of communications-enabled cameras could also be used to survey the locations of other sensor nodes in the scene such as temperature sensors, accelerometers or acoustic sensors. These location estimates could be used to better analyze and interpret the measurements derived from these sensors. Such a capability could be used in building monitoring applications where the sensor information could be used for energy management, airflow management, or intrusion detection.
A common feature of all such distributed imaging network applications is the need for each image acquisition node to be localized, that is, the need to know the position and orientation of each image acquisition node with respect to the other nodes.
Many prior art localization methods have used radio or acoustic signals, and monitored the time of flight, or the relative strength of the signals as a way of obtaining range information which can be used to recover the relative positions of the nodes in a network. Such techniques do not, however, allow the relative orientation of the imaging devices in the network to be easily calculated.